Abstract

The emissions from hot driving conditions, in which the exhaust-after-treatment systems are working properly, continue to decrease, which is why the emissions of cold starts have gained in importance. Traffic emission models are used to estimate and predict vehicle fleet emissions and the air quality of countries, regions, cities, etc. In addition to the statistical input of fleet activities, these models are mostly based on the use of separate emission sub-models for hot driving and cold start driving. In reality, the cold start models are almost entirely empirical and of limited accuracy. In this work, a model is developed that is based on physical reasoning, i.e., it is based on energy balances. Because many details, such as the thermal conductivities and the engine control decisions, are unknown, the model must be able to address different simplifications. The model can be parameterized with as few as two tests per vehicle. It is applied to several car samples (six to eight vehicles each) of different technical generations and shows reliable prediction for any combination of the driving pattern (including gradient), the ambient temperature, the stop time before the ride and the duration of the ride (if shorter than the warm-up phase).

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